Archive for the ‘spaces’ Category

h1

Natural and non-natural information and smart niches

December 3, 2018

The distinction between natural and non-natural information is highlighted by Laurence Kirmayer, that on my opinion helps to define the smartness concept in modern artificially enhanced systems. Particularly smartness is created by a loop – from self-organised individuals’ meanings, values and actions the data are aggregated and patterned using algorithms to form collective knowledge, and then these data are offered back as new affordances, action cues for the individuals. The human action niches are based on developing non-natural information cues and affinity to certain cultural memberships.

Grice (1957) distinguished between natural and non-natural forms of meaning, emphasizing the latter in most of his work. Natural meaning is a relation between two things that are correlated. Smoke ‘means’ fire because tokens of smoke reliably correlate with tokens of fire. Similarly, (certain kinds of) spots mean measles (understood not as the popular category but as the biomedically recognized infection with a particular virus). Non-natural meaning instead depends on the capacity of individual agents to exploit explicit and implicit social‘ conventions’(in the wide sense of locally shared norms, values and moral frames, expectations, ontologies, etc.) to infer the intentional states of other agents and thereby engage them or engage aspects of the environment with them. Red traffic lights, in virtue of convention (and law), ‘mean’ stop, and hence afford (and mandate) stopping — and this is made possible by the specifically human mastery of recursive inferences, both explicit and implicit, that agents make about other agents (Tomasello, 2014).

Different kinds of information (Piccinini, 2015; Piccinini & Scarantino, 2011; Scarantino & Piccinini, 2010).

‘Natural information’ obtains when a token informational vehicle x of kind X (that is, a sign, a pattern of neural activation, or what have you) carries natural information about some information source y of kind Y just in case there are reliable correlations between X and Y . Natural information, in other words, cannot misrepresent, for it is non-semantic; it is not the kind of thing that can be simply true or false.

‘non-natural information’ (or as we prefer to put it,‘conventional information’), pertains to semantic, content-involving representations that depend on social norms and cultural background knowledge. Non-natural information allows an agent to make a correct inference about some aspect of an intentional system, e.g., other agents, language and other symbolic systems such as mathematics, etc. Non-natural information is semantic in that it obtains in virtue of satisfaction conditions (e.g., truth conditions).

Kirmayer notes: “To operate with conventional affordances, agents must have shared sets of expectations — we must know what others expect us to expect.”

So smartness is not unconditional smartness but dependent of cultural constraints, it is a niche.

From https://www.academia.edu/26727261/Cultural_affordances_Scaffolding_local_worlds_through_shared_intentionality_and_regimes_of_attention

Advertisements
h1

Quieting the Niche – the withdrawal from the space of commons

December 3, 2018

Finn Brunton and Helen Nissenbaum have addressed the methodology of countersurveillance to digital surveillance by developing the notion of ‘obfuscation’, a means of neutralising corporate surveillance via data collection and analysis, whereby individuals utilise certain methods to—using an analogy from cybernetics— introduce ‘noise’ into their signals, in order to produce “misleading, false, or ambiguous data to make data gathering less reliable and therefore less valuable.” In the digital domain this involves reducing variety, concealing knowledge and intention, and evading identification and accountability, behaviours counterindicated by the necessities of maintaining cooperative epistemologies. The withdrawal from the space of commons and adversarial refusal of participation in the construction of the niche further erodes our collective ability to share, contribute to, and harness the systems of epistemically mediating technologies that underpin out collective systems, our cooperative cultures, and our ability to face the chance and uncertainty of the future.
The ethical and epistemological problems emerging as a result of the particular environmental affordances of ICT platforms are not simply a question of how we ought to use them, but are the real, systemic, ecological constraints on an environment that will determine the character and variety of possible modes of interaction.

From: Quieting the Niche: on Dataveillance and Everyday Resistance by Sam Forsythe
https://www.academia.edu/37900822/Quieting_the_Niche_on_Dataveillance_and_Everyday_Resistance?email_work_card=title&fbclid=IwAR3uTk3u38hNRA7bsTUTSz5FbuwcxY1_wSvQXLyJTutrW21ZFLd1eA0epa4

h1

Survey instrument: digital workers’ preferences of informal learning opportunities in socio-technical learning ecosystem

January 12, 2017

The survey was developed based on the informal learning interactions in workplaces described by Ley and associates [2014]. The survey items elaborated possible socio-technical system functionalities using the ideas from the prototypes of Learning Layers tools. The online survey comprised of three groups of statements that represent the socio-technical learning system dimensions for informal learning at work:

  1. Sensemaking statements: Learn & organize knowledge (11), Share knowledge (5), Annotate knowledge (5)
  2. Scaffolding statements: Search Resource (3), Find Resource (2), Awareness of resources (5), Find expert (4), Share help requests (2), Get expert Guidance (6)
  3. Knowledge maturing statements: Accumulate knowledge in system (5), Co-construct knowlede (7), Validate resources and experts with technology means (5)

ANNEX. Survey: Socio-technical learning ecosystem opportunities for informal workplace learning

SENSEMAKING
Learn and Reorganize knowledge

  • I find it useful identifying learning needs at work using the computer support
  • I find it useful revisiting the exciting learning moments later on
  • I find it useful taking records (notes, memos, reminders, photos, videos etc.) to capture my learning moments at work
  • I find it useful that learning records captured at work could be used for further learning.
  • I find it useful organizing the records of my learning moments into meaningful learning episodes
  • I find it useful making records of which tools/resources I have used at work
  • I find it useful reflecting (writing, audiotaping etc.) about learning records to make sense of what was learned
  • I find it useful organizing records of learning into personal portfolio
  • I find it useful collecting into personal portfolio learning resources about interesting topics
  • I find it useful composing different views of records in portfolio for different purposes.
  • 5I find it useful learning from videos of good practice and failure created by others

Annotate knowledge

  • I find it useful adding keywords/notes to my learning records
  • I find it useful organizing learning records/resources with tags/keywords suggested by the system

Share knowledge resources

  • I find it useful that my reflections about learning will become part of shared resources
  • I find it useful that author can decide the access and sharing rights for each record in the personal portfolio
  • I find it useful that each document could be shared with others for learning purposes
  • I find it useful sharing documents/folders with other professionals for learning
  • I find it useful sharing documents with other professionals across workplaces

SCAFFOLDING
Search knowledge resources

  • I find it useful searching the latest information about the topics of my learning interests
  • I find it useful using mobile devices for searching learning materials directly at work
  • I find it useful searching suitable learning materials from the shared system

Find knowledge resources

  • I find it useful finding learning materials related to my work easily during working
  • I find it useful to access my previous learning records when I need them during work

Awareness and recommending

  • I find it useful to get automatically notices about shared resources and learning activities of other professionals in my field
  • I find it useful to get automatical notices about the modifications of certain normatives or guidelines
  • I find it useful discovering new learning interests by getting notifications of learning interests and needs of others
  • I find it useful getting system suggestions of the most relevant learning materials that other users have considered useful
  • I find it useful using guidance materials created by other learners

Find expert

  • I find it useful expanding social networks with new experts
  • I find it useful of requesting help from my social network at work
  • I find it useful identifying trustful learning experts by their rank of the quality of help they have provided
  • I find it useful getting suggestions to expand my social network with relevant experts who can provide guidance

Get expert guidance

  • I find it useful negotiating problem/task context while receiving/providing guidance
  • I find it useful getting less guidance when competence increases
  • I find it useful mainly receiving guidance how to better organize my learning activities at work
  • I find it useful mainly receiving hints how to make sense of new knowledge in work context
  • I find it useful being guided by experts in using collective resources
  • I find it useful being guided by experts in using the objects and tools at work

Share help requests

  • I find it useful seeing the help requests from others that match with my expertise
  • I find it useful sharing the help requests in my social network to locate most relevant experts

KNOWLEDGE MATURING

Co-construct knowledge

  • I find it useful co-constructing new learning resources from different people’s contributions
  • I find it useful that learning resources can be improved by incorporating different viewpoints from experts
  • I find it useful that learning resources can be improved by integrating related resources
  • I find it useful improving official descriptions of work processes, normatives and guidelines by local networks of experts
  • I find it useful discussing normatives and guidelines locally among experts
  • I find it useful creating knowledge of work processes as a result of many contributors‘ efforts
  • I find it useful collecting knowledge of good guidance and support from actual guiding practices at workplaces

Validate with technology means

  • I find it useful that other professionals in the network can rate learning resources
  • I find it useful that other professionals in the network can endorse my competences
  • I find it useful endorsing personal expertise by networking peers
  • I find it useful rating or commenting learning materials from my task context to make them better contextualized
  • I find it useful rating experts based on provided guidance

Accumulate knowledge

  • I find it useful that everyone’s learning events can be automatically traced
  • I find it useful that each tool and learning material has digital records and use-histories.
  • I find it useful that digital documents would capture discussions about learning episodes around them
  • I find it useful that learning resources can collect discussions about them
  • I find it useful that learning resources can be improved by accumulating their use-histories
  • I find it useful that normative guidelines at work would consist of ‚official‘ immutable and ‚inofficial‘ mutable content
  • I find it useful influencing the collective knowledge by personal notes
  • I find it useful accessing the use-histories of objects, tools or digital learning resources
h1

Coherence and consistency in ecological learning

December 22, 2015

I have found an interesting PhD thesis by Jornet, Alfredo(2014)

https://www.duo.uio.no/bitstream/handle/10852/43305/PhD-Jornet-DUO.pdf?sequence=4&isAllowed=y

that reminded me my ideas of conceptual coherence and consistency in one paper that never was published. There in 2006  i wrote about conceptual coherence the following:

The definitions of conceptual coherence often combine the cohesiveness and consistency properties of conceptual knowledge. Coherence is a definition that is applicable for characterizing the states of the elements of some larger units (eg. phenomenological primitives, epistemological resources). Coherence is also related to the contextual and time-related dimensions. Cohesiveness is the property characterizing the conservation of inherent relationships among ideas in one explanation framework or the links among several related conceptual frameworks. Consistency is defined as a property indicating that students’ explanations of a certain phenomenon are stable, independently of the variable contexts that depend on the viewpoint of the explanation. It means that students are able of activating same locally coherent sets of ideas again and again in time, independent of task contexts.

That study in 2006 was conducted under the cognitivist (representational mental model) framework that i abandoned in next years being fascinated of distributed cognition and ecological learning models.

—————————

This PhD study looks coherence and continuity in the context of embodied and distributed cognition. It uses coherence and continuity to address the sense-making practices by means of which relations of signification are established within and across contexts and situations. Coherence denotes the achievement of order, whether within or across a given problematic or situation. Continuity refers more explicitly to the achievement of coherence across settings and activities, which has been traditionally investigated as the question of transfer.

The coherence and continuity of any set of ideas or concepts, as made relevant by the participants during joint activity, cannot be analyzed in terms of a priori formal properties of either the material setting (e.g., texts, graphs, demonstrations) or the individuals’ thinking (e.g., a learner’s mental representations of texts, graphs, or demonstrations), but must be treated as the result of material and practical operations that involve both.

The thesis suggests that several studies (bodily episodic feelings, that is, a bodily and context-bound sense of “having-been-there” (p. 311), it is only as part of addressing and being addressed by others during conversation that the initial connection comes to be developed as a conceptual one – Nemirovsky, 2011; context-sensitive concept projections and the transfer-in- pieces framework– diSessa & Wagner, 2005; Wagner, 2010) refer to the an expansion of their conceptualizations of learning beyond the individual mental abstract representation to better account for the intrinsic relation between subjects and their immediate material and social environments. A concept projection is “a set of knowledge elements with which a knower assimilates and interprets … the situation’s affordances in a particular, meaningful way” (Wagner, 2010, p. 450).”

Some interesting findings from this PhD study:

  • an initial sense of similarity motivates action that transforms the situation, which in turn allows for the eventual achievement of a new conceptual way of accounting for a new existing order.
  • Inference, as a cognitive process, does not precede, but rather is the outcome of, a larger unit of activity. 
  • Individuals constitute and are constituted by the establishment of conceptual coherence because they are subject to the objective changes that bodily activity brings about in their attunement to the accountable, collective organization of activity
  • Any assumption about what particular actions, utterances, artifacts, and representations “mean” as cultural tools needs to be set aside and instead requires taking a first-time-through perspective of the participants

————————-

Reading this PhD study and my old research made me think of my other thoughts about the formation of cultural patterns as niches, that may be described using both of these concepts – coherence and the consistency.

I think coherence and consistency are important both in the circles of personal pattern formation and stabilisation, as well as cultural pattern stabilisation, since both are formed as niches from instances of experiencing. So coherence in pattern or meaning niches requires to be formed across different contexts. How do these instances of experiences align themselves into the coherent pattern or meaning that we can perceive? Is it the distributed nature of those different context experiences that some ways form a consistent network like in the connectionist models? On the other hand how from the contextual coherence point of view do individuals activate cultural patterns and align them with own experienced patterns?

In my old paper i refer: “Hammer et al. (2004) used the term “framing“ to explain the activation of a locally coherent set of epistemological resources, which in the moment at hand would be activated in a mutually consistent and reinforcing way. Framing presumes distributed encoding among resources rather than accepting the notion that knowledge is located in any particular cognitive resource. Distributed encoding is the distributed interpretation across a network of cognitive elements, while the frames can often shift easily.

The consistency of patterns and meanings suffers from time delay and the bubble effect. So from the ecological learning point of view it is personally rather not useful to create consistent cognitive patterns but keeping them open to chance events that can destabilise them from coherency. I wonder how many recommender systems focus of destabilisation processes rather than stabilisation ones.

 

h1

systemic cognition and support in socio-technical systems

March 19, 2014

Explaining informal learning@work at managed clusters organized as TEL based socio-technical systems requires binding different level explanations: distributed cognitive level, personal – organizational level, cross-organizational network – cluster level.

ECOLOGICAL PRINCIPLES AND SYSTEMIC COGNITION

Systemic (or distributed) cognition level

Benefits: Focusing on the systemic nature of distributed cognition (on the interplay between the epistemic distributed cognition from the agents’ side and the collective distributed cognition of organizational or professional community cultures) allows using the ecosystem principles for describing how learning services emerge and co-exist in this informal workplace learning ecosystem.

Distributed cognition makes use of vector-spaces for describing cognitive niches of individuals, cultural niches and meaning niches of resources.

Person- Organization level

Benefits: to open up the transformative knowledge conversion between individual and organizational knowledge (Nonaka & Takeuchi, 1995); particularly utilizing agents’ informal learning events for the benefit of organization and motivating self-directed learning at work with social and (cross-)organizational factors.

Problems: Implementing new learning cultures in organizations, moving from unintentional towards intentional informal learning practices in organizations

Cluster and cross-organizational network level

Benefits: increased responsiveness for the cluster and for its member organizations is achieved through temporal cross- and inter-organizational informal learning activities at work, and orchestrated bottom-up and top-to-down systemic management of shared knowledge and provision of services based on the knowledge base (see IntelLEO project results for responsiveness).

Problems: competitive edge between members, sharing restrictions for knowledge, the lack of mutual trust or over-conficence in one’s organization’s knowledge

Workplace learning ecosystems

Basically, the systemic cognition approach views socio-technical systems at workplace learning as learning ecosystems.

There is a variety of learning services at present (created by experts and in general by any learner), which are used by other informal learners and that accumulate and interact at organization’s and cluster’s knowledge-bases.

Agents: novices and experts:

Scaffolding in networks requires considering the differences of agents’ problem contexts, knowledge and expertise.

Self-directed agents create and make use of (request for, validate, share, modify etc.) workplace learning service exemplars when they solve problems or provide help.

Each learning service exemplar provided or utilized must be fit to the prototypical learning services niche of his kind. These niches are determined by many exemplars that agents activate. For example, request for help must contain sufficient information about the specific problem and help needed to attract those help-providers that have suitable expertise for tackling this problem, further, the help provided to meet this request must be useful, it should solve this problem as closely as possible.

Knowledge transfer is primarily inter-personal.

Organization: At socio-technical system level certain prototypical learning services are dynamically provided, depending on which learning services the agents activate:

  • increased awareness for, accepting and forwarding help-requests;
  • providing help adaptively in turn-taking actions that ground the problem;
  • fading out the help when competence increases;
  • indicating towards developing helpful resources (artifacts, objects, tools, persons in the network);
  • validating resources;
  • increasing persons’ expertise and trust level in respect of providing help for learning at work.

Each prototypical learning service is directed towards solving some workplace problem or conceptualizing some idea. These prototypes have contextual meaning niches that emerge and change dynamically as a result of many agents’ activation of the exemplars of that kind. These meaning-niches are like communicative signals offloaded to the socio-technical system. They serve as attraction basins indicating to agents, where organizational learning could be most effective.

Organization:

  • creates incentives and manages motivation for promoting learning cultures at work;
  • explores and incorporates to organizational practices the usage of new learning@work activities;
  • removes the restrictions for cross-organizational knowledge transfer;
  • promotes open innovation cultures – open access to early prototypes,
  • design solutions or process-innovations with open source licenses;
  • promotes temporal alliances between members from different organizations to identify how to cope with challenges;
  • explore the opportunities or develop innovation.

Cluster management: maintains cluster’s organizational networks and knowledge base (ontologies, competences, norms and guidelines, access to human and virtual-real learning resources) and provides services based on this knowledge:

  • distributes information about challenges, practices and opportunities to learn;
  • identifies and nourishes new ideas that arise in the cluster organizations – such as organizing temporal cross-organizational knowledge-building activities for innovation;
  • provides, evolves and matures professional norms and guidelines;
  • initiates service-based value networks between member organizations;
  • detects proximities between cluster members;
  • promotes the learning culture at work that increases social motivation  – the more users are involved, the more likely it is that system becomes effective and is self-organizing;
  • controls organizational learning with incentives and motivation-management (policies for accreditation possibilities, and validation of workplace learning experiences).

Formal and informal cross-organizational networks are important to transfer knowledge.

The learning services the cluster can initiate depend on the abundance of certain learning service exemplars and of the learning service prototypes and niches at present in the socio-technical system.

Ecosystem principles applicable in learning ecosystems

The first principle in ecology is that the flow of energy and the exchange of matter through open ecosystem is regulated by the interactions of species (in our case types of learning services) and the abiotic component (by the web of energy and matter). Reyna conceptualized “teaching and learning” as this energy that empowers digital learning ecosystems to changing “information to knowledge”. The permeability of a digital learning ecosystem to the export and/or import of information and knowledge depend on the nature of the ‘architecture’ of the components of the system (e. g. connectivity, clustering), the characteristics of species, and their diversity and distribution, and interactions between them (such as commensalism).

The second important ecological principle is existence of the feedback loop to and from the environment that enables species to be adaptive to the environment and the environment to change as a result of species. A recent literature in evolutionary theory elaborates the notion of niche construction as an ecological factor that enables organisms to contribute for and benefit from environmental information. If organisms evolve in response to selection pressures modified by themselves and their ancestors, there is feedback in the system. In our approach to digital learning ecosystems, the “service-species” are activated by users with different roles (learner, facilitator) and their learning intentions. The niches for each service-species in the digital ecosystem may be collected from user-behavior, for example by learning analytics (an emerging approach to tracing digital footprints of learners and groups, visualizing the learning-related patterns).

Applications in social semantic systems: 

Niches are vector spaces – see paper From vector spaces to meanings

If we make use of the Connectionism approach to concept-processing (see the paper of Seitlinger et al, 2013) and extend this approach to epistemic and collective distributed cognition that happens in using mobile learning tools together with social semantic server, we may have an approach for socio-semantic recommendations that provide help based on the meaning niches that fit best to the requests (see the examples below).

In biology the figures for niche breadth figures are used, that may be useful in recommendation, also the idea of fitness landscape and attraction basins may be considers in recommendations.

The third important principle that we extend from ecology to technology-enhanced learning domain is associated with the communicative interactions between species. The digital community is a naturally occurring group of “service-species” populations in e-learning ecosystem who inhabit the same habitat (but use different niches) and form temporary coalitions (communities). For example the mutualisms such as parasitism, symbiosis or commensalism may appear between service species are associated with sharing the resources and associate with our first principle (energy and matter exchanges in the network). Other type of interactions, based on communication, which assumes mutual awareness, signaling between agents (or using the accumulated signals left into the environment) may be distinguished as well.

Application cases of informal learning at work

Below, there are three informal learning and supporting behaviours that may potentially appear in socio-technical systems.

RECEIVING HELP FROM EXPERTS

To introduce new knowledge to the newcomers the experts make use of their earlier experiences, they also utilize and evolve resources for providing help, as well as the archetypical scaffolding models in their profession, on the other hand, the help-provision increases the trust level of experts in respect of solving certain problems.ACCUMULATING EXPERTISE

VALIDATING SOLUTIONS

Recommending – relating systemic cognition and connectionist approaches

Some issues of recommending when using the systemic (distributed) cognition approach:recommending

Seitlinger. et al., (2013). Recommending Tags with a Model of Human Categorization

Seitlinger et al.(2013) use in their recommendation model Connectionist model of cognitive processing:

Kruschke 1992 alcove model

First layer can have distributed activation. The model is initialized with equal attention strengths to all dimensions, but as the training proceeds, the model learns to allocate more attention to relevant dimensions and less to irrelevant dimensions.

Internal layer functions as agent’s cognitive niche that incorporates cultural niche for weighting. Internal layer gives weights to the nodes, each hidden node corresponds to a position in the multidimensional space. A state of activation (a) at a given time (t): The state of a set of units is usually represented by a vector of real numbers a(t). These may be binary or continuous numbers, bounded or unbounded. A frequent assumption is that the activation level of simple processing units will vary continuously between the values 0 and 1.

In biology, Hutchinson (1957) defined niche as a region (n-dimensional hypervolume) in a multi-dimensional space of environmental factors that affect the welfare of a species (in our case prototypes). Niches have been conceptualized as the collections of environmental gradients with certain ecological amplitude, where the ecological optimum marks the gradient peaks where the organisms (in our case exemplars) are most abundant.

The welfare of species can be determined by meaning-creation and action-taking possibilities in the environment.

In the gradient concept structural ecosystem properties are comprehended as concentration gradients in space and time (Müller, 1998). Any niche gradient is a peak of the fitness landscape of one environmental characteristic (Wright, 1931), which can be visualized in two-dimensional space as a graph with certain skew and width, determining the ecological amplitude. The shape of the fitness graph for certain characteristic can be plotted through the abundance of certain specimen (exemplar in our case) benefitting of this characteristic. All niche gradients are situated and establish a multi-dimensional hyper-room, which axes are different environmental parameters.

This connectionist theory problem was also explained by T. Ley in Innsbruck meeting.

Also see article From vector spaces to meanings

h1

thesis: Learning and knowledge building practices for teachers’ professional development in an extended professional community

July 7, 2013

Kairit Tammets, my first doctoral student will defend her thesis at 21st of August.

Now her dissertation is available from here http://e-ait.tlulib.ee/330/1/tammets_kairit.pdf

Tammets, Kairit (2013) Learning and knowledge building practices for teachers’ professional development in an extended professional community.

The purpose of her PhD research project is to investigate the process of the learning and knowledge building (LKB) in the extended professional community that is supported with the socio-technical system.
h1

Spatial narratives in new media ecosystems

November 13, 2012

Two years ago i held a speech on Spatial narratives in Media Mutations conference in Bolognia. Now they will publish a book in italian, and i have rewritten my conference speech with The Shadow of The Wind example, which will appear in the book in italian. Here is the english version of the paper: